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Register a new userCrucial stages of protein folding through a solvable model: predicting target sites for enzyme-inhibiting drugs
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Added by
Cristian Micheletti
Publication date
2002
fields
Physics
and research's language is
English
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An exactly solvable model based on the topology of a protein native state is applied to identify bottlenecks and key-sites for the folding of HIV-1 Protease. The predicted sites are found to correlate well with clinical data on resistance to FDA-approved drugs. It has been observed that the effects of drug therapy are to induce multiple mutations on the protease. The sites where such mutations occur correlate well with those involved in folding bottlenecks identified through the deterministic procedure proposed in this study. The high statistical significance of the observed correlations suggests that the approach may be promisingly used in conjunction with traditional techniques to identify candidate locations for drug attacks.
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A general strategy is described for finding which amino acid sequences have native states in a desired conformation (inverse design). The approach is used to design sequences of 48 hydrophobic and polar aminoacids on three-dimensional lattice structures. Previous studies employing a sequence-space Monte-Carlo technique resulted in the successful design of one sequence in ten attempts. The present work also entails the exploration of conformations that compete significantly with the target structure for being its ground state. The design procedure is successful in all the ten cases.
A theoretical model for the folding of proteins containing disulfide bonds is introduced. The model exploits the knowledge of the native state to favour the progressive establishment of native interactions. At variance with traditional approaches based on native topology, not all native bonds are treated in the same way; in particular, a suitable energy term is introduced to account for the special strength of disulfide bonds (irrespective of whether they are native or not) as well as their ability to undergo intra-molecular reshuffling. The model thus possesses the minimal ingredients necessary to investigated the much debated issue of whether the re-folding process occurs through partially structured intermediates with native or non-native disulfide bonds. This strategy is applied to a context of particular interest, the re-folding process of Hirudin, a thrombin-specific protease inhibitor, for which conflicting folding pathways have been proposed. We show that the only two parameters in the model (temperature and disulfide strength) can be tuned to reproduce well a set of experimental transitions between species with different number of formed disulfide. This model is then used to provide a characterisation of the folding process and a detailed description of the species involved in the rate-limiting step of Hirudin refolding.
We develop a theoretical approach to the protein folding problem based on out-of-equilibrium stochastic dynamics. Within this framework, the computational difficulties related to the existence of large time scale gaps in the protein folding problem are removed and simulating the entire reaction in atomistic details using existing computers becomes feasible. In addition, this formalism provides a natural framework to investigate the relationships between thermodynamical and kinetic aspects of the folding. For example, it is possible to show that, in order to have a large probability to remain unchanged under Langevin diffusion, the native state has to be characterized by a small conformational entropy. We discuss how to determine the most probable folding pathway, to identify configurations representative of the transition state and to compute the most probable transition time. We perform an illustrative application of these ideas, studying the conformational evolution of alanine di-peptide, within an all-atom model based on the empiric GROMOS96 force field.
In this work we have studied, with the help of a simple on-lattice model, the distribution pattern of sites sensitive to point mutations (hot sites) in protein-like chains. It has been found that this pattern depends on the regularity of the matrix that rules the interaction between different kinds of residues. If the interaction matrix is dominated by the hydrophobic effect (Miyazawa Jernigan like matrix), this distribution is very simple - all the hot sites can be found at the positions with maximum number of closest nearest neighbors (bulk). If random or nonlinear corrections are added to such an interaction matrix the distribution pattern changes. The rising of collective effects allows the hot sites to be found in places with smaller number of nearest neighbors (surface) while the general trend of the hot sites to fall into a bulk part of a conformation still holds.
Drug resistance to HIV-1 Protease involves accumulation of multiple mutations in the protein. Here we investigate the role of these mutations by using molecular dynamics simulations which exploit the influence of the native-state topology in the folding process. Our calculations show that sites contributing to phenotypic resistance of FDA-approved drugs are among the most sensitive positions for the stability of partially folded states and should play a relevant role in the folding process. Furthermore, associations between amino acid sites mutating under drug treatment are shown to be statistically correlated. The striking correlation between clinical data and our calculations suggest a novel approach to the design of drugs tailored to bind regions crucial not only for protein function but also for folding.
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